Identification and Estimation of Industry Dynamic Models with Persistent and Hidden State Variables

本研究项目的重点是生产者进入、增长和退出的结构模型的制定和估计。数据来源是新的；一个酒精类纳税申报单文件，其中包含德克萨斯州所有有执照的餐馆和酒吧的出生日期、离职日期和酒精销售额的完整月度历史记录。在该模型中，一家公司的销售额与其利润成正比，但短暂的成本冲击使其不能完美地反映盈利能力的持久组成部分。由于这种不完美的观察，模型的状态变量既是持久的，又是隐藏的。状态变量的持久性使该模型有别于许多可估计的动态离散选择模型，这些模型结合了Rust(1987)的条件独立性假设。为了理清盈利能力的持久性和暂时性因素，该项目利用了这样一个事实，即生产者的退出决定只取决于持久性因素。在具有正态分布冲击的模型中，生产者退出决策中的信息确定了描述盈利能力的永久性和暂时性组成部分以及生产者的最优退出门槛的参数。本研究项目的一个重要组成部分是将这种辨识证明推广到半参数和非参数环境。该项目最初的实证研究侧重于区分与Jovanovic(1982)类似的创业学习高斯模型与具有完美创业信息的模型，如HOpenhayn(1992)。数据集中描述每个餐厅或酒吧的位置及其母公司特征的其他信息表明，该模型和估计技术进一步泛化。

This research project focuses on the formulation and estimation of structural models of producer entry, growth, and exit. The data source is new; a file of alcohol tax returns that contains the date of birth, date of exit, and a complete monthly history of the dollar value of alcohol sales for all licensed restaurants and bars in Texas. In the model, a firm's sales is proportional to its profits, but transitory cost shocks make it an imperfect indicator of profitability's persistent component. Because of this imperfect observation, the model's state variable is both persistent and hidden. The state variable's persistence distinguishes this model from the many estimable models of dynamic discrete choice that incorporate Rust's (1987) conditional independence assumption. To disentangle the persistent and transitory components of profitability, this project uses the fact that producers' exit decisions depend only on the persistent component. In the model with normally distributed shocks, the information in producers' exit decisions identifies the parameters describing both the persistent and transitory components of profitability as well as the producer's optimal exit threshold. An important component of this research project is the extension of this identification proof to semi-parametric and non parametric environments. The project's initial empirical research focuses on distinguishing Gaussian models of entrepreneurial learning similar to Jovanovic's (1982) from models with perfect entrepreneurial information, such as Hopenhayn's (1992). Additional information in the data set describing each restaurant or bar's location and the characteristics of its parent firm suggest further generalizations of the model and estimation technique.